I thought I’d finish off this short series of Python Backtesting Mean Reversion by providing a full, executable script that incorporates the use of SQL queries to extract our ticker symbols from the SQLite database we created in an earlier post (This can be found here)

In this particular example I have decided to run a series of backtests on ticker symbols from the database, based upon a “Niche” of “Gold Miners”. In theory this selection of tickers based upon some non-arbitrary, meaningful grouping criteria should allow us to focus in on pairs of symbols that are more likely to have statistically meaningful co-integration of prices series.